Skin cancer is the most common cancer in North America. Over 550,000 new cases of skin cancer are diagnosed each year. One in seven Canadians will develop a skin cancer during their lifetime. If detected early, skin cancer can be cured by relatively minor surgical removal. However, if detected late, more extensive and disfiguring surgery becomes necessary. It is especially important to diagnose malignant melanoma early. If treatment for malignant melanoma is commenced too late, systemic metastasis and death can occur.
At present, skin cancers are detected primarily by visual inspection by physicians. However, clinical accuracy of visual diagnoses is 75% at best. Definitive diagnosis is therefore based on histological examination of skin biopsy. Excisional biopsy currently remains the most reliable diagnostic approach for the early detection of skin cancer, but is invasive and impractical for screening high-risk patients who may have multiple suspicious lesions. Many unnecessary biopsies are done, at considerably cost to the health care system. Moreover, some needed biopsies may not be performed because of a failure to recognize a cancer.
During skin cancer treatment, visual assessment is also relied upon to determine the extent of the tumor, and therefore the amount of tissue to be either excised or irradiated. If a tumor has margins that are poorly defined, it may be necessary to perform repeated biopsy procedures from multiple sites in a time-consuming, expensive, and tedious procedure known as Mohs micrographic surgery.
Following skin cancer treatment, ongoing patient monitoring by visual inspection and periodic microscopic examination is required for detecting recurrent tumor or de novo skin cancer at other sites. All stages in the management of skin cancer would be facilitated by techniques that could provide accurate diagnostic information without requiring multiple expensive and potentially disfiguring skin biopsies.
A variety of approaches for noninvasive diagnosis of the skin have been developed using either optical or non-optical methods. Non-optical methods include ultrasound and MRI, while skin reflectance, autofluorescence, and thermography involve measurement of cutaneous optical properties that are altered in disease states. Many groups in the world are working to develop reflectance skin imaging methods (analogous to digital photography) for improving the early detection of skin cancer using digital processing. This approach has improved the registration, recording, and documentation of skin lesions, but has not yet significantly improved the accuracy of non-invasive diagnoses.
Raman spectroscopy and fluorescence spectroscopy have both been suggested as tools for the diagnosis of cancers. Raman spectroscopy measures the wavelength and intensity of light which has been scattered inelastically from molecular systems. Raman scattered light has wavelengths that are shifted from that of the incident light by amounts corresponding to the energies of excitations of the molecular systems. The excitations are typically vibrations.
Raman scattered light is typically relatively faint. When monochromatic light strikes a sample, almost all the observed light is scattered elastically (Rayleigh scattering) with no change in energy (or wavelength). Only a very small portion of the scattered light, typically approximately 1 part in 108, is inelastically scattered (Raman scattering). Raman peaks are typically narrow and in many cases can be attributed to the vibration of specific chemical bonds (or normal modes dominated by the vibration of a functional group) in a molecule. As such, a Raman spectrum provides a “fingerprint” for the presence of various molecular species. Raman spectroscopy can be used for both qualitative identification and quantitative determination of molecular species.
Raman spectra have been observed from various biological tissues including skin. Identified Raman scatterers in tissues include elastin, collagen, blood, lipid, tryptophan, tyrosine, carotenoid, myoglobin, nucleic acids etc. Raman spectroscopy has also been used to monitor cutaneous drug delivery and pharmacokinetics during skin disease treatment. It has been used to monitor blood analytes, e.g. glucose, lactic acid, and urea, in blood samples.
Most studies which have investigated the Raman spectra of tissues have investigated ex vivo tissue samples using Fourier-Transform (FT) Raman spectrometers. FT-Raman systems take up to ½ hour to acquire a spectrum and are bulky and not portable, and therefore are of limited clinical utility. Recently developed dispersive type Raman systems based on fiber optic light delivery and collection, compact diode lasers, and high efficiency spectrograph-detector combinations, have shortened the time required to obtain a Raman spectrum to minutes or sub-minutes.
In addition to scattering and reflecting light, tissues can also absorb light and emit the absorbed energy in the form of fluorescent light that is of a longer wavelength than the incident light. Such “autofluorescence” signals are weak but can be detected. Fluorescence excitation and emission studies of tissues are usually performed in the ultraviolet and visible wavelength ranges.
Recently, some tissue autofluorescence studies have been conducted at longer red to near infrared (NIR) wavelengths. Some examples are Zhang G, et al., Far-red and NIR Spectral Wing Emission from Tissues under 532 and 632 nm Photo-excitation Lasers in Life Science 9:1-16, 1999 and Demos S G, et al. Tissue imaging for cancer detection using NIR autofluorescence, Proceedings SPIE 4613:31-34, 2002.
A problem with the evaluation of pigmented lesions, including melanoma and its precursors, by reflectance or visible fluorescence techniques is that melanin is a strong light absorber throughout the ultraviolet and visible spectrum. Both incident and reflected or re-emitted (fluorescent) photons in this wavelength range are largely absorbed by melanin. This results in weak spectra and “black hole” images that provide little clinically useful information.
Richards-Kortum et al., U.S. Pat. No. 6,095,982; discloses the use of a combination of fluorescence and Raman spectroscopy in detecting pre-cancers and other abnormalities in tissue. The fluorescence measurements are made in the ultraviolet while the Raman spectroscopy measurements are made in the infrared. Richards-Kortum et al, U.S. Pat. Nos. 5,991,653; 5,697,373; 5,612,540 and 6,258,576 disclose similar methods.
Verma U.S. Pat. No. 4,832,483 discloses a method for using Raman spectroscopy for the detection of cancers. Georgakoudi et al. U.S. Pat. No. 6,697,652 disclose a method for evaluating tissue using multiple spectroscopic techniques including fluorescence, reflectance and light scattering spectra. Nordstrom et al. U.S. Pat. No. 6,385,484 discloses the use of fluorescence spectra and reflectance spectra for classifying tissue specimens. Tumer et al. U.S. Pat. No. 6,135,965 discloses the use of neural networks to identify spectra corresponding to abnormal tissues.
Alfano et al. U.S. Pat. No. 5,293,872 relates to methods which include the use of Rarnan spectroscopy for distinguishing between calcified atherosclerotic tissue and fibrous atherosclerotic tissue. Alfano et al., U.S. Pat. No. 5,131,398 discloses a method which uses native fluorescence for distinguishing cancerous tissue from benign tumour tissue. Alfano et al., U.S. Pat. No. 5,261,410 discloses a method for using Raman spectroscopy for determining whether a tissue is a malignant tumour tissue, a benign tumour tissue or a normal tissue. Alfano et al., U.S. Pat. No. 5,369,496 discloses the use of back-scattered light for evaluating tissue samples.
Puppels et al., WO 2004/051242 discloses the use of high-wavenumber Raman spectroscopy for detecting abnormalities in tissue. Haaland et al., U.S. Pat. No. 5,596,992 discloses the use of multivariate classification techniques applied to infrared spectra from cell and tissue samples. Gellermann et al. U.S. Pat. No. 6,205,354 discloses the use of Raman spectroscopy for detection of carontenoids. Lin et al., U.S. Pat. No. 6,377,841 disclose the use of fluorescence and diffuse reflectance spectra for detecting the boundaries of brain tumours. Garfield et al., U.S. Pat. No. 5,450,857 discloses the use of fluorescence spectra for measuring cervical dilation. Boppart et al. U.S. Pat. No. 6,485,413 discloses a instrument which can be used for collecting various spectra including fluorescence spectra and Raman spectra.
Empirically determined diagnostic algorithms based on the determined peak intensities, widths, and/or peak ratios of tissue spectra have been described in literature for evaluating variations in tissue spectra with tissue pathology. Some examples are Mahadevan-Jansen A, and Richards-Kortum R. Raman spectroscopy for the detection of cancers and precancers, J Biomed Opt 1996; 1, 31-70; Mahadevan-Jansen A, et al. Near-infrared Raman spectroscopy for in vitro detection of cervical precancers Photochem Photobiol 1998; 68:123-132; and, Huang Z, et al., Near-infrared Raman spectroscopy for optical diagnosis of lung cancer, Int J Cancer, 2003; 107:1047-1052.
Multivariate statistical techniques have been applied for similar purposes. Examples include: Bakker Schut TC et al. In vivo detection of dysplastic tissue by Raman spectroscopy Anal Chem 2000; 72:6010-6018; Mahadevan-Jansen A, et al. Near-infrared Raman spectroscopy for in vitro detection of cervical precancers Photochem Photobiol 1998; 68:123-132; Stone N, et al. Near-infrared Raman spectroscopy for the classification of epithelial pre-cancers and cancers, J Raman Spectrosc 2002; 33: 564-573; Deinum G, et al., Histological classification of Raman spectra of human coronary artery atherosclerosis using principal component analysis, Appl Spectrosc 1999; 53:938-942; and, Silveira L Jr et al., Correlation between near-infrared Raman spectroscopy and histopathological analysis of atherosclerosis in human coronary arteries, Lasers Surg Med 2002; 30:290-7.
To date, none of the diagnostic methods described in the publications listed above have been widely adopted for use in tissue screening.
Despite the large amount of research that has been done in the area, there remains a need for fast, accurate cost-effective methods and apparatus capable of screening for tumours or other cancerous lesions.